Hello, I am Anjul Tyagi

PhD candidate in the Visual Analytics and Imaging Lab at Stony Brook University advised by Prof. Klaus Mueller. Get in touch, connect me on LinkedIn!

My research interest includes:

  • 3D Object Detection on Point Clouds (#Self Driving Cars, #Computer Vision, #Deep Learning)
  • Automated Infographics Generation (#Data Visualization, #Computer Vision, #Deep Learing)
  • Deep Neural Network Architecture Search (#Deep Learning, #Optimization)
  • High Dimensional Data Visualization (#Data Visualization)

Besides research, I like contributing to interesting Open Source Projects on Github, and writing about latest research trends on Medium. I have been fortunate to collaborate with professors and researchers in – Computer Vision at Seagate, Data Visualization (Klaus Mueller-SBU, Jian Zhao-UWAT), Storage Systems (Erez Zadok-SBU) and Eye Tracking (Ayush Kumar-SBU, Michael Burch-TU/e).

Socially, I love meeting new people and enjoy part time Fitness, Athletics and Music. Connect me on Instagram!

Fun Fact! My academic lineage traces back to Isaac Newton and Galileo Galilei. Here’s how.

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News

  • I am on the top writers list on Medium for the topic of Self-Driving Cars. Thanks to my team at Seagate.
  • Started working with Seagate Technologies as a Data Analyst and Machine Learning Intern.
  • I’ll be giving a talk at At&t Labs Graduate Student Symposium this year in NYC.
  • Presented ICE at VIS 2019.
  • Travel Award from IACS to attend IEEE VIS.
  • Young writer award for the ICE paper.
  • Successfully defended my qualifier RPE (Research Proficiency Exam) exam.
  • Attended a social event at Google’s NYC office.
  • Date of my Research Profeciency Exam decided (Aug 28th). I’ll be completing my second year of Ph.D.
  • NSF Grant for my research in Storage Systems Optimization is approved.
  • ICE accepted for VAST Conference Track at IEEE VIS.
  • I’ll be serving as a Student Volunteer at ETRA 2019.
  • User Task Classification paper accepted at ACM ETRA 2019.
  • Storage Systems Research paper accepted at USENIX HotStorage workshop.